Performance Generalization in Biometric Authentication Using Joint User-Specific and Sample Bootstraps
Norman Poh and Samy Bengio
IEEE Trans. Pattern Analysis and Machine Intelligence
Biometric authentication performance is often depicted by a decision error trade-off (DET) curve. We show that this curve is dependent on the choice of samples available, the demographic composition and the number of users specific to a database. We propose a two-step bootstrap procedure to take into account of the three mentioned sources of variability. This is an extension to the Bolle et al's bootstrap subset technique. Preliminary experiments on the NIST2005 and XM2VTS benchmark databases are encouraging, e.g., the average result across all 24 systems evaluated on NIST2005 indicates that one can predict, with more than 75\% of DET coverage, an unseen DET curve with 8 times more users. Furthermore, our finding suggests that with more data available, the confidence intervals become smaller and hence more useful.
|Additional Information:||biometric authentication, verification|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Deposited By:||Norman Poh|
|Deposited On:||07 October 2006|